Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method.Through a series of novel design concepts,including the integration of a detecting circuit and an analog-to-digital converter,a miniaturized functional electrical stimulation circuit technique,a low-power super-regeneration chip for wireless receiving,and two wearable armbands,a prototype system has been established with reduced size,power,and overall cost.Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects,the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy.Test results showed that wrist flexion/extension,hand grasp,and finger extension could be reproduced with high accuracy and low latency.This system can build a bridge of information transmission between healthy limbs and paralyzed limbs,effectively improve voluntary participation of hemiplegic patients,and elevate efficiency of rehabilitation training. Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy. A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method. Through a series of novel design concepts, including the integration of a detecting circuit and an analog-to-digital converter, a miniaturized functional electrical stimulation circuit technique, a low-power super-regeneration chip for wireless receiving, and two wearable armbands, a prototype system has been established with reduced size, power, and overall cost.Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects, the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy. Test results showed that wrist flexion / extension , hand grasp, and finger exte nsion could be reproduced with high accuracy and low latency. This system can build a bridge of information transmission between healthy limbs and paralyzed limbs, effectively improve voluntary participation of hemiplegic patients, and elevate efficiency of rehabilitation training.